A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks

Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydra...

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Main Authors: Juan Francisco Fuentes-Pérez, Ana García-Vega, Francisco Javier Bravo-Córdoba, Francisco Javier Sanz-Ronda
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/20/6909
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author Juan Francisco Fuentes-Pérez
Ana García-Vega
Francisco Javier Bravo-Córdoba
Francisco Javier Sanz-Ronda
author_facet Juan Francisco Fuentes-Pérez
Ana García-Vega
Francisco Javier Bravo-Córdoba
Francisco Javier Sanz-Ronda
author_sort Juan Francisco Fuentes-Pérez
collection DOAJ
description Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (<i>Keras + TensorFlow</i>), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability.
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spelling doaj.art-f7a0a3845aac4acabd132d643baf17832023-11-22T19:59:24ZengMDPI AGSensors1424-82202021-10-012120690910.3390/s21206909A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor NetworksJuan Francisco Fuentes-Pérez0Ana García-Vega1Francisco Javier Bravo-Córdoba2Francisco Javier Sanz-Ronda3Department of Hydraulics and Hydrology, ETSIIAA, University of Valladolid, 34004 Palencia, SpainCentro Tecnológico Agrario y Agroalimentario Itagra.ct, 34004 Palencia, SpainCentro Tecnológico Agrario y Agroalimentario Itagra.ct, 34004 Palencia, SpainDepartment of Hydraulics and Hydrology, ETSIIAA, University of Valladolid, 34004 Palencia, SpainStepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (<i>Keras + TensorFlow</i>), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability.https://www.mdpi.com/1424-8220/21/20/6909water-level sensorslow-costhydraulic modelingfishwaysneural networksclogging
spellingShingle Juan Francisco Fuentes-Pérez
Ana García-Vega
Francisco Javier Bravo-Córdoba
Francisco Javier Sanz-Ronda
A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
Sensors
water-level sensors
low-cost
hydraulic modeling
fishways
neural networks
clogging
title A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
title_full A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
title_fullStr A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
title_full_unstemmed A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
title_short A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
title_sort step to smart fishways an autonomous obstruction detection system using hydraulic modeling and sensor networks
topic water-level sensors
low-cost
hydraulic modeling
fishways
neural networks
clogging
url https://www.mdpi.com/1424-8220/21/20/6909
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